![]() ![]() ![]() Open mpi.jam located at C:\boost_1_60_0\tools\build\src\tools\mpi.jam and revise the following lines of code: Before using the b2 command a configuration file needs to edited to include the MPI library inside the Boost build. Therefore, CMake and Visual Studio are not used to build and install the library. Unlike the other dependencies and libraries that will be built in this tutorial, Boost comes with its own simplified build procedure called b2. Prepare Boost 1.60 for Build – Download Boost 1.60 in the link provided above and extract the zip file to an easy to reach destination (For me, it was C:\boost_1_60_0).Once MPI has been install, we begin the Boost build process. exe file and C:\Program Files (x86)\Microsoft SDKs\MPI for the. Download the newest version of Microsoft MPI (Version 7) using the above link into their default installation location ( C:\Program Files\MPI for the. Therefore, before building the Boost library, Microsoft MPI needs to be installed. Install Microsoft MPI Library – One of the requirements for PCL is that Boost be built with Microsoft MPI support.Microsoft MPI v7 (msmpisdk.msi and MSMpiSetup.exe).Therefore, two libraries need to be downloaded for this process. For PCL on Windows, the Boost library needs to be built with Microsoft MPI support. The Boost library is a free peer-reviewed portable C++ source library. If you do not have these installed yet, you can download them here:īuilding and Installing Boost 1.6.0 Using b2 Compiler All of the libraries that will be built above, except for Boost, are built using CMake and Visual Studio 2013. Therefore, the PCL libraries and all of its dependencies will be built for the 64-bit machine. The PCL build used in my research and this tutorial is the 64-bit version. Test PCL Library in Visual Studio Using Example Program.Build and Install PCL Using Cmake and Visual Studio.Build and Install VTK 6.3.0 with Qt Support Using Cmake and Visual StudioĪfter each of the above dependencies have been built and installed the PCL library can be built.Build and Install Qhull 2015.2 Using Cmake and Visual Studio.Build and Install Eigen 3.2.7 Using Cmake and Visual Studio.Build and Install Flann 1.8.4 Using Cmake and Visual Studio.Build and Install Boost 1.60 Using b2 Compiler.The steps taken to successfully build and install the PCL library and its dependencies include: In this post, the build procedures for each dependency as well as the PCL library itself will be described. The PCL library has several dependencies that need to be built or installed beforehand with the same compiler used to build the PCL library. So, for future reference and for those who need to do the same, this is a description of the build and installation process for PCL on Windows using Visual Studio 2013. It took me several days, as the instructions on the PCL website were not very detailed. It turns out it was much harder than my previous experience building a custom library (OpenCV + Python) as it has many dependencies that need to also be custom built with the same Visual Studio version. ![]() Therefore, I had to build and install my own version of PCL. The problem was, the installers were built on an older version of Visual Studio. It looked very promising so I decided to use it. Having very little experience with 3D reconstruction, I went on a search for possible libraries to use and stumbled upon the Point Cloud Library. I’m at a point in my research where I need to register points I’ve segmented from a series of ultrasound images in a single 3D reconstruction of a target area.
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